Materials and objects typically analyzed visually using an imaging system may be analyzed using image acquisition systems capable of handling multiple samples using some level of automation. Such image acquisition systems typically include a light source (such as for example, a white light or a fluorescent light source), a multiple sample plate, and an objective lens optically coupled to an image recording medium (or for example, a camera) to capture an image of the sample that may be substantially magnified. The multiple sample plate may rest or fit onto a sample-positioning mechanism that moves the plate in the optical path of the light source and objective lens. Examples of automated multiple-sample imaging systems include for example, microscopes and analyzers, such as analyzers that may use imaging for analysis of images captured in performing assays. One example of a type of automated imaging system is a high content screening system in which the high-resolution imaging and analysis of samples is automated. The analysis may entail recognizing and segmenting objects, and extracting the features of interest for high content image analysis typically requires the use of high content visualization tools. One particular example of a high content screening system is the Leica HCS A made by Leica Microsystems.
Image acquisition systems may acquire images of samples placed in multiple sample plates implemented as microwell or microplates having a plurality of wells or cavities. It is noted that alternative terms, such as for example, “microwell,” “microtiter,” and “microplate,” are used herein as reference to the plates. The samples are placed in wells arranged in a matrix within the microwell plate.
The Leica HCS A uses a software component called the High Content Screening LAS AF (“Leica Application Suite Advanced Fluorescence”) MATRIX M3 automation software. The Leica HCS A system also includes a confocal microscope system. The LAS AF MATRIX M3 automation software includes an autofocus function that permits acquisition of images, which may be used to generate a focus map. A focus map is an automatically generated three-dimensional image showing true sample topology. The focus map is used for Z-positioning of the object of interest during the scan. According to the size and planarity of the samples, the optimal number and positions of the autofocus points is defined.
Another example of an imaging system is the CellReporter™, which is manufactured by Molecular Devices, LLC. The CellReporter™ includes high-quality, quantitative, data image analysis software to image, analyze, and report on individual cells. In capturing images for analysis, the CellReporter™ creates a 3D topological map, or surface map, of the plate-cell attachment surface. Prior to imaging the samples, each plate is scanned while images obtained thereafter are displaying the overall base of the plate. The surface map is used to represent the whole plate contours. In this particular application, the surface map is used to maintain focus across each plate during imaging to eliminate the need to focus at each well before taking an image.
The conventional microplate structure comprises a specimen plate portion with wells or cavities, and a bottom plate portion. The well bottom, or surface at the bottom of each well, is the plate-cell attachment surface of each well. The surface of the microplate opposite the well bottoms is the plate bottom. The distance between plate bottom and the well bottoms defines the thickness of the microplate. The thickness of the microplate may range between about 10 μm and about 1500 μm depending on the manufacturer.
The structure and specification of the microplates play an important role when used in the system to record images with high resolution (X, Y resolution to 100 nm, Z resolution to 300 nm) and high magnification (with 4× magnification and higher). Certain problems in obtaining in-focus images of the wells with samples therein are caused by out-of-focus light measurements. In particular, the problem in obtaining un-focused images in the well with samples is caused by incorrect determination of the focal plane. The incorrect assignment of the focal plane may be caused by variations in the microtiter plates' properties, for example flatness or the thickness of the plate.
The microplates may comprise between 6 and 1536 sample wells or cavities. Such plates are manufactured by a number of companies using a variety of materials. The flatness of the well bottoms and of the plate bottom varies substantially, not only from one manufacturer to another but even from different manufacturing lots. The thickness of the microplate typically varies substantially along the surface of the plate, which may result in incorrect assignment of the focal plane during images.
The importance of the microplate well flatness in obtaining high quality images has been noted by researchers and manufacturers. For example, researchers at GE Healthcare Bio-Sciences Corporation evaluated the 96 and 384-well MartiPlate™ by performing the same assays on a number of microplates so that the biological evaluations on the different plates under test could be compared. Imaging background measurements were made on all plates by measuring fluorescence intensity background areas of selected images; average background gray levels were measured on a selected number of wells in each plate. Plate flatness data was obtained taking the .xdce file output from each image stack, which contained information on the autofocus position for each image. The information on the autofocus position for each image was used to produce a surface plot for each type of plate. The flatness of the plate well was assessed by taking measurements from several fields of view across three wells in each plate type. For each plate type, positions were abstracted from the .xdce file and plotted as a bar graph. The variation of the autofocus position within a given well reveals its flatness deviation.
This method may be used to label microplates with flatness characteristics, which enables a user to select microplates with desired flatness characteristics. However, a number of manufacturers are not conducting this type of experiment with their microplates, or characterizing their microplates in terms of flatness. Flatness characterization has not been made a part of their process for microplate evaluation, and accordingly, flatness characteristics are not part of the manufacturing specifications of the microplates. Moreover, the different manufacturing processes of the microplates make it difficult or impossible to provide the flatness characteristics for the plate bottom and for the bottom of the wells within the plate.
Therefore, there is a need for automated measurement and visualization of microwell plate information on the flatness of the bottom of the plate and the bottom of the wells for obtaining high quality images in high content screening of samples.
There is also a need for improved and efficient evaluation and presentation of microplate properties, especially with respect to the variation of the thickness along the microplate bottom portion via automated measurements, and to display these properties for acquiring “in focus” microscopy images.